Important business decisions often revolve around comprehension of complex data sets in the context of some business goal. For example, a company may use database and spreadsheet applications to track profitable and unprofitable assets over a particular calendar year using multidimensional sets of data that may include partner data, customer data, or other information. Video processing methods and rendering programs provide algorithms that can process multiple dimensions of a complex data set as part of rendering a visualization. For example, a user may use a visualization of a projected trend in attempts to understand the highly complex nature of the vast numbers of values to track or plot. Data reduction methods can be used to reduce the complex data by creating new dependent variables. For example, sales and expense data can be reduced and visualized in terms of profit or loss which may be more meaningful to the end-user. However, many of the available applications are limited to pre-set interface control types and static user interaction features.